2305 07605 Generative AI: Implications and Applications for Education

Although the term might initially seem coarse, Frankfurt’s philosophical exploration of “bullshit” provides a deeply nuanced perspective. Central to Frankfurt’s analysis is the stark differentiation between a liar and a bullshitter. While the former has a conscious relationship with the truth, deliberately choosing to conceal or distort it, the latter exhibits a sheer disregard for truth.

This would allow students to receive more targeted and effective support and achieve better learning outcomes. By the time the summit was held on Feb. 15, ChatGPT had reached more than 100 million unique users, and 30% of all college students had used it for assignments, making it one of the fastest-ever applications ever adopted overall – and certainly in education settings. Within the education world, teachers and school districts have been wrestling with how to respond to this emerging technology.

Content Creation for Courses

How might these educational goals inform students’ interactions not only with educators, but also with AI tools moving forward? One participant proposed that the large language model could Yakov Livshits be guided to behave in this way through prompts. Prompts could tell the model how to respond, for example, by asking students leading questions and not just giving answers to questions.

If You Can’t Beat Them, Join Them: Teachers Are Going All In on … – Impakter

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Posted: Mon, 18 Sep 2023 13:32:44 GMT [source]

MagicSchool’s Khan says the threadbare legacy of education technology causes some teachers to be skeptical of new AI services. “It’s an industry that’s been burned by technology over and over again,” he says. In her own AI training sessions for educators, she has encountered other teachers who question whether automating part of their job qualifies as cheating. Murphy responds that it’s no different than pulling things off the internet with a web search—but that just as for any material, teachers must carefully check it over. “It’s your job to look at it before you put it in front of kids,” she says, and verify there’s no bias or illogical content. Ednovate has signed up for the paid version of MagicSchool, even though Murphy says roughly 10 percent of Ednovate teachers she encounters worry AI will take their jobs and replace them.

Techopedia Explains Generative AI

AI can also automate administrative tasks, freeing up valuable time for educators to focus on student engagement and critical thinking. Acknowledging AI and its uses in higher education is a crucial, pragmatic step toward equipping students with the skills they need to thrive once they leave our campuses. LLMs have many promising educational uses, but they are general purpose tools. The affordances of a product like ChatGPT and the specific needs of educators are not always aligned.

generative ai in education

Even though generative AI is a relatively new buzzword among technology enthusiasts, one of its applications is quite familiar to even the laymen. Deepfake videos started appearing on the internet as pranks initially but they have started gaining momentum in mainstream media as well as movies. Deepfake technology is being made available to all in the form of software tools such as FakeApp, DeepFaceLab,.and Zao, Wombo, Reface, among others are some deepfake apps that people use just for fun. Recently a deepfake video of President Volodymyr Zelensky stating that he will lay down arms and return to his family has been broadcasted on Ukrainian news that was hacked. Technology can be used for both good and bad and Deepfake technology is another perfect such example that has the potential to be exploited for malicious activities.

Title:Generative AI: Implications and Applications for Education

Yakov Livshits
Founder of the DevEducation project
A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.

Within the classroom context, there was less emphasis on high-level policymaking and greater attention towards steps tech firms could take, as well as changes that could occur at the school district level. Participants agreed that responsible developers should create a mechanism to enable the quick and reliable identification of an output as artificially generated. But they also recognized that classifier tools are likely to be imprecise and insufficient for the use cases and that school policies and practices will need to adapt to how students use AI tools. Furthermore, there Yakov Livshits may be significant benefits to be gained by integrating these new technologies into teaching and learning instead of trying to prevent them. Students are often assessed via their writing; ‘the essay’ has historically been treated as  a key hallmark of academic rigor and performance–from elementary through graduate school. However, as expectations for students shift with the increasing integration of LLMs into the classroom, the very purpose of learning vis-à-vis tasks such as writing – which has been instrumental to the educational status quo – is brought into question.

generative ai in education

The discriminator’s job is to evaluate the generated data and provide feedback to the generator to improve its output. Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and accelerate progress towards SDG 4. However, rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. UNESCO is committed to supporting Member States to harness the potential of AI technologies for achieving the Education 2030 Agenda, while ensuring that its application in educational contexts is guided by the core principles of inclusion and equity. It aims to shift the conversation to include AI’s role in addressing current inequalities regarding access to knowledge, research and the diversity of cultural expressions and to ensure AI does not widen the technological divides within and between countries. The promise of “AI for all” must be that everyone can take advantage of the technological revolution under way and access its fruits, notably in terms of innovation and knowledge.

The models used for text generation can be Markov Chains, Recurrent Neural Networks (RNNs), and more recently, Transformers, which have revolutionized the field due to their extended attention span. Text generation has numerous applications in the realm of natural language processing, chatbots, and content creation. The digital divide between students with and without access to technology may also be exacerbated by the use of generative AI in education, potentially widening the learning gap for underserved and minority students.

Guidance for generative AI in education and research – UNESCO

Guidance for generative AI in education and research.

Posted: Thu, 07 Sep 2023 13:41:38 GMT [source]

Schools and policymakers who wish to protect children from the disruptions posed by LLMs might create restrictive policies. Educators are often overworked and many school systems are severely under-resourced. Collaborations with AI firms should not strain educational stakeholders further; it is often appropriate to provide material incentives for participating teachers.

I mean, I’m being playful about this, but I think the point is that AI doesn’t understand any of the questions that it’s asking but it can ask the questions, and then the child can start to think deeper than just regurgitating the story. So there’s all sorts of possibilities here that we just have to think of as new wine instead of asking how can AI automate our order thinking about teaching and learning. And people don’t remember this, but there was a time when– before search engines when people really struggled to find resources, and there was enormous excitement when search engines came out. They are based on AI at the back end, coming up with lists of things that hopefully match what you typed in. In fact, the problem with the search engine becomes not trying to find anything, but trying to filter everything to decide what’s really useful.

This, in turn, can lead to those biases and prejudices becoming embedded in the AI itself. Because of the enormous volume of data needed to train generative AI systems, it is typically infeasible to have humans vet all the training data. Additionally, if the system is designed to continue learning from user queries and responses over time, those inputs will generally be outside the control of the system developers. This is particularly concerning in an education context where students may be using these tools to learn more about the world around them, meaning the tool may impart or reinforce biases in students’ thinking.

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